基于去趋势波动分析的不同特征音乐刺激下脑电特性

doi:10.12066/j.issn.1007-2861.2163

摘要/Abstract

摘要：

旨在研究受试者对不同特征音乐的心理生理反应, 探索脑电长程关联特性. 招募 10 名在校学生作为受试者, 参与 4 种具有不同物理特征的音乐聆听任务, 并完成自我情绪评价, 同步采集受试者任务期间的头皮脑电信号. 针对音乐刺激脑电的非平稳非线性特性, 使用一种检测非平稳时间序列的长程相关性非线性方法——去趋势波动分析, 通过计算脑电信号分频段序列的标度指数分析脑电信号长程相关性, 并结合行为学数据, 探究不同音乐特征对情绪加工的影响. 实验结果显示, 升调版欢快乐曲诱发的积极情绪感受会显著降低, 而无论升调还是降调都会显著降低悲伤音乐诱发的悲伤情绪效应; 在不同音调特征的音乐刺激诱发下, 受试者在 alpha, beta 频段上还表现出明显大脑偏侧化特点, 左半球脑动力表现更活跃. 所应用的标度指数可以反映不同音乐刺激下脑电的特异性.

关键词: 情绪音乐, 脑电, 去趋势波动分析, 偏侧化

Abstract:

In this study, we investigated the effects of different musical features on the electrophysiological and psychological responses of participants, and explored the long-range correlations of electroencephalograms (EEGs). We recruited 10 students to participate in four listening tasks involving different musical features. After each task, the participants completed a self-evaluation of their emotions. Scalp EEG signals were collected synchronously during the tasks. Considering the non-stationary and nonlinear characteristics of music-stimulated EEGs, we used a nonlinear method to detect the long-range correlation of non-stationary time series, namely, detrended fluctuation analysis. Long-range correlations were analysed by calculating the scale index of the EEG signal sub-band sequence, and combining it with behavioural data. The results show that the positive emotions induced by the rising tone of the happy version are significantly reduced, and whether it was rising tone or falling tone, it would significantly reduce the sad emotions induced by sad music. Under musical stimulation involving different tonal features, the subjects showed obvious brain lateralisation characteristics in the alpha and beta bands, with the left hemisphere brain dynamics showing greater activity. Moreover, the scale index used in this study was shown to reflect the specificity of EEG under different musical stimuli.

Key words: emotional music, electroencephalogram (EEG), detrended fluctuation analysis, lateralisation

中图分类号:

R318.0

朱嘉诚, 李颖洁. 基于去趋势波动分析的不同特征音乐刺激下脑电特性[J]. 上海大学学报(自然科学版), 2021, 27(3): 514-524.

ZHU Jiacheng, LI Yingjie. Electroencephalogram features based on detrended fluctuation analysis of different features of music stimulation[J]. Journal of Shanghai University（Natural Science Edition）, 2021, 27(3): 514-524.

图/表 10

图1

表1

表2

图2

图3

图4

图5

图6

表3

表4

参考文献 28

[1]	Balasubramanian G, Kanagasabai A, Mohan J, et al. Music induced emotion using wavelet packet decomposition: an EEG study[J]. Biomedical Signal Processing and Control, 2018,42:115-128. doi: 10.1016/j.bspc.2018.01.015
[2]	Panksepp J, Bernatzky G. Emotional sounds and the brain: the neuro-affective foundations of musical appreciation[J]. Behavioural Processes, 2003,60(2):133-155. doi: 10.1016/S0376-6357(02)00080-3
[3]	Banerjee A, Shankha S, Anirban P, et al. Study on brain dynamics by non linear analysis of music induced EEG signals[J]. Physica A: Statistical Mechanics and its Applications, 2016,444:110-120. doi: 10.1016/j.physa.2015.10.030
[4]	Lordier L, Loukas S, Frédéric G, et al. Music processing in preterm and full-term newborns: a psychophysiological interaction (PPI) approach in neonatal fMRI[J]. Neuro Image, 2018,185:857-864.
[5]	Rajendran V G, Teki S, Schnupp J W. Temporal processing in audition: insights from music[J]. Neuroscience, 2017,389:4-18. doi: 10.1016/j.neuroscience.2017.10.041
[6]	Sundeep T. A citation-based analysis and review of significant papers on timing and time perception[J]. Frontiers in Neuroscience, 2016,10:330-340.
[7]	Poikonen H, Alluri V, Brattico E, et al. Event-related brain responses while listening to entire pieces of music[J]. Neuroscience, 2016,312(15):58-73. doi: 10.1016/j.neuroscience.2015.10.061
[8]	Arjmand H A, Hohagen J, Paton B, et al. Emotional responses to music: shifts in frontal brain asymmetry mark periods of musical change[J]. Frontiers in Psychology, 2017,8:1-13.
[9]	Archi B, Shankha S, Anirban P, et al. Study on brain dynamics by non linear analysis of music induced EEG signals[J]. Physica A: Statistical Mechanics and its Applications, 2016,444(15):110-120. doi: 10.1016/j.physa.2015.10.030
[10]	Sakharov D, Davydov V, Pavlygina R. Intercentral relations of the human EEG during listening to music[J]. Human Physiology, 2005,31(4):392-397. doi: 10.1007/s10747-005-0065-5
[11]	Hausmann M, Hodgetts S, Eerola T. Music-induced changes in functional cerebral asymmetries[J]. Brain and Cognition, 2016,104:58-71. doi: 10.1016/j.bandc.2016.03.001 pmid: 26970942
[12]	宋蓓, 侯建成. 婴儿音乐基本认知能力的发展及大脑偏侧化机制研究[J]. 音乐探索, 2015,4:129-137.
	Song B, Hou J C. Infants' development of basic cognitive ability of music and its function of brain's laterality[J]. Explorations in Music, 2015,4:129-137.
[13]	Li S T K, Hsiao H W. Music reading expertise modulates hemispheric lateralization in English word processing but not in Chinese character processing[J]. Cognition, 2018,176:159-173. doi: 10.1016/j.cognition.2018.03.010
[14]	Tsai C G, Chou T L, Li C W. Roles of parietal and dorsal premotor cortices in relative pitch processing: comparing musical intervals to lexical tones[J]. Neuropsychologia, 2018,119:118-127. doi: 10.1016/j.neuropsychologia.2018.07.028
[15]	Peng C K, Havlin S, Stanley H E, et al. Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series[J]. Chaos: An Interdisciplinary Journal of Nonlinear Science, 1995,5(1):82-87. doi: 10.1063/1.166141
[16]	陈拥军, 曾敏, 尧德中. 多道脑电信号时间序列的非线性动力学分析[J]. 癫痫与神经电生理学杂志, 2001,10(1):28-31.
	Chen Y J, Zeng M, Yao D Z. The nonlinear dynamic analysis with multi-channel EEG time series[J]. Journal of Clinical Electroneurophysiology (China), 2001,10(1):28-31.
[17]	Bachmann M, Päeske L, Kalev K, et al. Methods for classifying depression in single channel EEG using linear and nonlinear signal analysis[J]. Computer Methods & Programs in Biomedicine, 2018,155:11-17.
[18]	王春方, 张力新, 刘爽, 等. 基于去趋势波动分析 (DFA) 的脑卒中后抑郁症静息脑电特征提取与识别[J]. 中国生物医学工程学报, 2013,32(5):520-525.
	Wang C F, Zhang L X, Liu S, et al. Feature extraction and recognition of resting EEG in post stroke depression subjects based on detrended fluctuation analysis[J]. Chinese Journal of Biomedical Engineering, 2013,32(5):520-525.
[19]	Zhu Y, Yu S, Huang D, et al. Identification of a novel DFA Ⅰ-producing inulin fructotransferase from streptomyces davawensis[J]. International Journal of Biological Macromolecules, 2016,92:723-730. doi: 10.1016/j.ijbiomac.2016.07.092
[20]	Sakamoto J T, Liu N, Koh Z X, et al. Integrating heart rate variability, vital signs, electrocardiogram, and troponin to triage chest pain patients in the ED[J]. American Journal of Emergency Medicine, 2017,36(2):185-192. doi: 10.1016/j.ajem.2017.07.054
[21]	Rodrigues S F, Brito A A, De C, et al. Detection of the persistency of the blockages symmetry influence on the multi-scale cross-correlations of the velocity fields in internal turbulent flows in pipelines[J]. Physica A: Statistical Mechanics and its Applications, 2018,509:294-301. doi: 10.1016/j.physa.2018.06.009
[22]	毛茅. 音乐诱发情绪的心理生理测量及其在服务设计中的应用[D]. 北京: 清华大学, 2013.
[23]	刘冲, 赵海滨, 李春胜, 等. 脑电信号频带能量特征的提取方法及分类研究[J]. 系统仿真学报, 2012,24(12):2496-2499.
	Liu C, Zhao H B, Li C S, et al. Research on band power extraction and classification of EEG signal[J]. Journal of System Simulation, 2012,24(12):2496-2499.
[24]	Peng C K. Mosaic organization of DNA nucleotides[J]. Physical Review E, 1994,49(2):1685-1689. doi: 10.1103/PhysRevE.49.1685
[25]	Russell J A. Core affect and the psychological construction of emotion[J]. Psychological Review, 2003,10(1):145-172.
[26]	Altenmüller E, Schürmann K, Lim V K, et al. Hits to the left, flops to the right: different emotions during listening to music are reflected in cortical lateralisation patterns[J]. Neuropsychologia, 2002,40(13):2242-2256. pmid: 12417455
[27]	Nikulin V V, Brismar T. Long-range temporal correlations in alpha and beta oscillations: effect of arousal level and test-retest reliability[J]. Clinical Neurophysiology, 2004,115(8):1896-1908. pmid: 15261868
[28]	Nikulin V, Brismar T. Long-range temporal correlations in electroencephalographic oscillations: relation to topography, frequency band, age and gender[J]. Neuroscience, 2005,130(2):549-558. pmid: 15664711